• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2005.10a
• /
• pp.338-341
• /
• 2005

In this paper, we present analytic forms of the ordered weighted averaging (OWA) operator weighting functions, each of which has properties of rank-based weights and a constant level of orness, irrespective of the number of objectives considered. These analytic forms provide significant advantages for generating OWA weights over previously reported methods. First, OWA weights can be efficiently generated by use of proposed weighting functions without solving a complicated mathematical program. Moreover, convex combinations of these specific OWA operators can be used to generate OWA operators with any predefined values of orness once specific values of orness are α priori stated by decision maker. Those weights have a property of constant level of orness as well. Finally, OWA weights generated at a predefined value of orness make almost no numerical difference with maximum entropy OWA weights in terms of dispersion.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.12 no.6
• /
• pp.727-732
• /
• 2009

In this paper, the dependence of the Kalman filter-based emitter location algorithm on the initial estimate is investigated. Given all the LOB data, the initial estimate of the emitter location is obtained from the linear LSE algorithm with the former LOB data. Using the initial estimate, the Kalman filter algorithm is applied with the remaining LOB data to update the initial estimate. It is shown that as the number of data used in the calculation of the initial estimate increases, the accuracy of the final estimate is improved and the total computational complexity of obtaining the initial estimate and the final estimate increases. In addition, the dependence of the performance of the Kalman filter algorithm on the predefined constant is illustrated.

• Journal of Electrical Engineering and Technology
• /
• v.1 no.1
• /
• pp.63-72
• /
• 2006

The purpose of this raper is to address the negative impedance instability in DC/DC converters. We present the negative impedance instability of PWM DC/DC converters loaded by constant power loads (CPLs). An approach to design digital controllers for DC/DC converters Is presented. The proposed method, called Power Alignment control technique, is applied to DC/DC step-down choppers operating in continuous conduction or discontinuous conduction modes with CPLs. This approach uses two predefined state variables instead of conventional pulse width modulation (PWM) to regulate the output voltage. A comparator compares actual output voltage with the reference and then switches between the appropriate states. It needs few logic gates and comparators to be implemented thus, making it extremely simple and easy to develop using a low-cost application specific integrated circuit (ASIC) for converters with CPLs. Furthermore, stability of the proposed controllers using the small signal analysis as well as the second theorem of Lyapunov is verified. Finally, simulation and analytical results are presented to describe and verify the proposed technique.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2000.04b
• /
• pp.347-354
• /
• 2000

The seismic behaviors of a bridge system with several simple spans are examined to see the effects of the longitudinal stiffness degradation due to abutment-soil interaction. The abutment-backfill system is modeled as one degree-of-freedom-system with nonlinear spring and linear damper. various soil-conditions surrounding the abutment such as loose sand, medium dense sand, and dense sand are considered in the bridge seismic analysis. The idealized mechanical model for the whole bridge system is modeled by adopting the multiple-degree-of-freedom system, which can consider components such as pounding phenomena, friction at the movable supports, rotational and translational motions of foundations, and the nonlinear pier motions. The stiffness of the abutment is found to be rapidly reduced at the beginning of the earthquakes, and to be converged to constant values shortly after the displacement approaches to the Predefined critical values. It is observed that the maximum relative distanced an maximum relative displacements are generally Increased as the relative density of a soil decreases As the peak ground acceleration increases, the response ratio of the case considering stiffness degradation to the case considering constant stiffness decreases.

• Journal of Korea Multimedia Society
• /
• v.6 no.7
• /
• pp.1139-1148
• /
• 2003

Biometric system has been studied as an optimal solution for preventing or reducing the peculation or loss of ID. Nowadays, face recognition has been spot-lighted as a future biometric system because it is not forced to contact the part of human body with the specific input area of the system. However, there is some limitations to get the constant facial features because the size of face area is varied by the capturing distance or tilt of the face. In this paper, we can extract constant facial features within the predefined threshold using the simple geometric processing such as image scaling, transformation, and rotation for frontal face images. This face recognition system identifies faces with 92% of accuracy for the 400 images of 40 different people.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.05a
• /
• pp.166-169
• /
• 2002

The accuracy in maneuvering target tracking using multiple models is caused by the suitability of each target motion model to be used. The interacting multiple model (IMM) algorithm and the adaptive IMM algorithm require the predefined sub-models and the predetermined acceleration intervals, respectively, in consideration of the properties of maneuvers to construct multiple models. In this paper, to solve these problems intelligently, a genetic algorithm (GA) based-IMM method using fuzzy logic is proposed. In the proposed method, a sub-model is represented as a set of fuzzy rules to model the time-varying variances of the process noises of a new piecewise constant white acceleration model, and the GA is applied to identify this fuzzy model. The proposed method is compared with the AIMM algorithm in simulations.

• Journal of KSNVE
• /
• v.7 no.4
• /
• pp.621-629
• /
• 1997

For computer aided design and costruction of low noisy power plants, indoor and outdoor noise prediction program has been developed. The program utilizes the predefined data of noise sources and building materials and has the faculty to estimate the source level using the empirical formula in case of the measured data not being available. In the noise prediction, the mutual noise propagation between indoor and outdoor sites are considered. The outdoor noise source in the calculation of geometric divergence effects is modelled as the omni-directional finite line or planar source according to the source geometry and the receiving points. Outdoor noise prediction is carried out to consider the diffraction effect due to plant structures as well as the attenuation effect due to atmospheric absorption and soft ground. The results of indoor and outdoor noise prediction for a recently constructed diesel engine power plant show good agreement with the measured.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.9
• /
• pp.1103-1111
• /
• 1999

STACOM will be utilized to control substation voltage in the near future. Although STACOM shows good voltage regulation performance owing to its rapid and continuous response, it needs additional reactive power compensation device to keep control margin for emergency such as fault. ULTC transformer is one of good candidates. This paper presents a Kohonen Neural Network (KNN) based coordination control scheme of ULTC transformer and STACOM. In this paper, the objective function of the coordination control is minimization of both STACOM output and the number of switchings of ULTC transformer while maintaining substation voltage magnitude to the predefined constant value. This coordination, control is performed based on reactive load trend of the substation and KNN which offers optimal tap position in view of STACOM output minimization. The input variables of KNN are active and reactive power of the substation, current tap position, and current STACOM output. The KNN is trained by effective Iterative Condensed Nearest Neighbor (ICNN) rule. This coordination control applied to IEEE 14 bus system and shows satisfactory results.

• Proceedings of the KIEE Conference
• /
• 2002.07d
• /
• pp.2382-2384
• /
• 2002

The accuracy in maneuvering target tracking using multiple models is caused by the suitability of each target motion model to be used. The interacting multiple model (IMM) algorithm and the adaptive IMM (AIMM) algorithm require the predefined sub-models and the predetermined acceleration intervals, respectively, in consideration of the properties of maneuvers in order to construct multiple models. In this paper, to solve these problems intelligently, a genetic algorithm (GA) based-IMM method using fuzzy logic is proposed. In the proposed method, the acceleration input is regarded as an additive noise and a sub-model is represented as a set of fuzzy rules to model the time-varying variances of the process noises of a new piecewise constant white acceleration model. The proposed method is compared with the AIMM algorithm in simulations.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.52 no.1
• /
• pp.16-21
• /
• 2003

The accuracy in maneuvering target tracking using multiple models is resulted in by the suitability of each target motion model to be used. The interacting multiple model (IMM) method and the adaptive IMM (AIMM) method require the predefined sub-models and the predetermined acceleration intervals, respectively, in consideration of the properties of maneuvers in order to construct multiple models. In this paper, to solve these problems, a genetic algorithm(GA) based-IMM method using fuzzy logic is proposed. In the proposed method, the acceleration input is regarded as an additive noise and a sub-model is represented as a set of fuzzy rules to calculate the time-varying variances of the process noises of a new piecewise constant white acceleration model. The proposed method is compared with the AIMM algorithm in simulation.